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Abstract

This study demonstrates that formal institution networks are antecedent to firms adopting coopetition to improve performance. The influence of formal institution agents to foster coopetition within an industry is driven by fragilities in the institutions of emerging economies. We studied the Brazilian healthcare sector, which is characterized by strong regulation and government support. We analyzed how and to what extent coopetition relates to formal institution agents and the performance of private healthcare operators. The study employs a quantitative methodology with a sample of 149 firms from the Brazilian private healthcare system through partial least squares structural equation modelling (PLS-SEM). Our findings highlight that networks facilitated by formal institution agents precede firms’ adoption of coopetition to enhance performance. They also underscore the impact of regulatory policy on firms’ strategies and behaviors in the healthcare sector. Our findings emphasize that formal institution networks alone do not guarantee performance improvement. Healthcare firms must develop coopetitive strategies to create and capture value within these relationships. Our study sheds light on the organizational dynamics within the Brazilian private healthcare sector and provides insights for managers and policymakers. For policymakers, it highlights opportunities and challenges in enhancing healthcare sector competitiveness, emphasizing the importance of considering the institutional environment. For healthcare firm managers, it details opportunities for developing coopetitive strategies. Finally, the study is subject to boundary conditions potentially limiting the generalizability of its findings to a broader global context. Additionally, it is also limited by the cross-sectional design since respondents’ replies are specific to the current scenario in the healthcare sector.

Keywords

coopetition performance formal institution agents networks healthcare industry

Introduction

Coopetition has been regarded as a theory (Gnyawali & Ryan Charleton, 2018) that can explain situations in which organizations compete and cooperate simultaneously at different levels (Albert-Cromarias & Dos Santos, 2020). This concept has been discussed concerning to the healthcare sector since the beginning of the 2000s (Gee, 2000) and, more recently, about integrated healthcare networks (Raus et al., 2018). However, such studies have rarely considered the relevance of public policies or government intervention and the few that have done so were mainly conducted in the private sector. For example, Merck and Johnson & Johnson recently entered a government-brokered partnership to broaden the capacity to manufacture and supply of SARS-CoV-2/COVID-19 medicines and vaccines (Rowland & McGinley, 2021).

Formal institution agents (FIA) are organizations that provide legitimacy to firms, grant access to resources such as technical support, and improve economic returns (Regnér & Edman, 2014). According to Monticelli et al. (2021), formal institution agents work as cooperation hubs to grow markets, operate as policymakers, or induce cooperation between competitors through formal legal structures, and may be governmental or private organizations.

The healthcare system in Brazil is characterized by its complexity, asymmetry, and fragmentation, with strong regulation and government support. Public and private operators aim to serve the population through the Brazilian Unified Health System (SUS), recognized as the world’s most extensive universal and free healthcare system. The SUS is managed by the Brazilian Ministry of Health, which is responsible for transferring funds to states, municipalities, and university hospitals, among other care providers. Both the management and the operations of SUS care have been decentralized to states and municipalities, accounting for approximately 46% of public health expenditure in Brazil (Vasconcellos, 2015). In parallel, total spending on healthcare increased from 7 to 8.3% of the country’s Gross Domestic Product (GDP) from 2000 to 2014 (Massuda et al., 2018). The government’s share of this total health expenditure equated to 47%, while the private sector accounted for 53% (Alliance Experts, 2019). However, only 30% of the Brazilian population has private healthcare coverage (Carrança, 2018).

Brazil’s National Supplementary Health Agency (Agência Nacional de Saúde Suplementar [ANS], 2021) is a formal institution agent that interferes in the competitive strategies of companies, aiming to balance public and private interests, since while it is responsible for ensuring that the quality of service provided by the private system is maintained, it also has a mission to ensure that the sector is an attractive investment option since the SUS does not have to provide care to people who have private coverage. The ANS illustrates how formal institution agents can use mechanisms to protect or encourage an industry while stimulating the development of coopetitive strategies such as public-private partnerships (Mariani & Kylänen, 2014). In sectors with high levels of competition and cooperation, such as the health industry, formal institution agents can encourage coopetitive strategies based on resource complementarity or create barriers to new entrants. The dynamism of such relationships enables them to progress due to the interdependence between firms and formal institution agents, thus enabling cost reduction, promotion of relationships, learning, and positioning through differentiation (Hidalgo et al., 2022). Nonetheless, strengthening the industry’s competitiveness may come at the expense of other participants who do not align with these strategies.

This study aims to analyze the influence on the performance of private health plan operators in Brazil of coopetition fostered by formal institution agents. We use the theoretical lens of the relational view (Dyer & Singh, 1998), considering coopetition behavior as an essential resource for firm performance (Crick & Crick, 2021a). We also draw on institutional theory (North, 1990) to explain how the intrinsic tension of networks formed between competitors is reduced, thus allowing coopetitive strategies. The analysis focuses on Brazilian health plans and health insurance firms. Our analysis unit is therefore the private operators of health plans that adopt coopetitive strategies to promote their competitiveness.

We identified different challenges, and we applied the coopetitive strategy to fill these research gaps. First, the evidence on how coopetition affects firm performance available in the literature is still inconclusive (Raza-Ullah, 2021). Some empirical studies have examined the effect of coopetition on firm performance using just a single financial indicator (Kim & Parkhe, 2009; X. Luo et al., 2006) or a measure of value creation in inter-firm alliances (Rai, 2016), while others have done so by analyzing firms’ innovation performance (Park et al., 2014; Ritala, 2012), their business performance by competitive position (Crick & Crick, 2021a), or their export intensity (Crick & Crick, 2021b). However, studies rarely consider a multidimensional concept of performance. Second, our research takes an original viewpoint. Although there are a small number of studies investigating coopetition in healthcare systems such as MedUnite (Walters, 2012), Taiwanese health networks (Peng & Bourne, 2009), and French healthcare providers (Albert-Cromarias & Dos Santos, 2020), there is a need for additional research considering the healthcare sector (McCarthy et al., 2018). Moreover, there is a particular need for a study investigating emerging economies with weak institutions, since these markets are known for their inefficient regulatory and legal organizations, capricious policies, and poor infrastructure (Hoskisson et al., 2000). Third, researchers have rarely attempted to understand how coopetitive strategies function in this type of industry or done so taking the influence of institutions into account. This is relevant to understanding the strategies and policies employed by firms and formal institution agents to promote efficiency in the system (Macinko & Harris, 2015; Monticelli et al., 2023), mainly so that private healthcare operators must optimize resources, skills, and experiences (Papastathopoulou & Hultink, 2012).

The study makes three main contributions. First, we showed how coopetition can optimize resource utilization (Y. Luo, 2004), enhance strategic positioning (Ritala, 2012), and create economies of scale while reducing risks and leveraging resources jointly among competitors (Gnyawali & Park, 2009, 2011; Ritala & Hurmelinna-Laukkanen, 2009). Second, we offer a novel coopetition perspective by exploring the private healthcare system that attends to the population’s primary needs. Brazilian government has applied increasing regulatory pressures over recent decades, imposing a growing list of responsibilities on private healthcare providers (Baird, 2019). Competing operators have resorted to cooperation in response to government pressure while improving their operational efficiency, As a result, the cost of health plans has fallen. Thirdly, our study diverges from the traditional research perspective, such as Czakon (2018), as it examines coopetition through the lens of formal institution agents. We demonstrate that formal institutional agents wield significant influence over the coopetitive strategies employed by private companies.

The paper is divided into seven further sections. Section 2 presents the theoretical background to the study and introduces our hypotheses; section three details the methodology; sections four and five set out the results, which are discussed in section 6; section seven covers the conclusions we have drawn from our findings, acknowledging its limitations and suggesting avenues for further research.

Theoretical Background

Previous research has related firms’ performance-enhancing outcomes to their resources and capabilities, including hard resources (tangible assets), and soft resources (intangible assets) (Crick, 2020). This perspective focuses on the value, rarity, inimitability, and non-substitutability of resources needed to achieve a sustainable competitive advantage (Barney, 1991). In the context of coopetition studies, Crick and Crick (2021a) indicated a need to consider the level of flexibility of firms facing uncertain markets. Moreover, Barney (2018) highlighted the role stakeholders, including rivals, played in organizational performance. Previous studies have connected dynamic capabilities like absorptive capacity with their antecedents and determinants (Ponce-Espinosa et al., 2020), presented a coopetition capability that moderates the relationship between the coopetition paradox and external tension (Bengtsson et al., 2016), and explained how coopetition capability is developed and can be institutionalized to achieve coopetition (Hoffmann et al., 2018).

In this sense, the institutional approach, focuses on how organizations are influenced by internal and external normative pressures that cause them to be guided by legitimized elements, such as standard operating procedures for professional certification, state requirements, or operational processes for survival and growth (Zucker, 1987). In practice, firms share norms that shape behavioral rules and collective procedures (North, 1990). These logics reduce the intrinsic tension of coopetition networks; institutions promote, facilitate, and stimulate networks since they can mediate the interplay within economic sectors. Thus, we believe that institutional approach provides mechanisms to explain how coopetition outcomes can be enhanced through Network of Formal Institution Agents (NWFI) since they stimulate interplay and create a favorable environment for coopetition networks. Consequently, institutional approach can unpack the drivers of coopetition activities and their effect on improvement of firm performance.

We study the healthcare sector because it encompasses all stages from healthcare, regarding specialized treatments to basic care (Raus et al., 2018). Consequently, providers that supply the public health system must deal with a fixed annual budget, different from the private system where the gains can be increased and later divided (Barretta, 2008). The relationship between performance, formal institution agents, and the coopetition network in the healthcare sector is complex and significantly influences the operational environment of firms in this industry (Macinko & Harris, 2015).

Previous studies have related coopetition networks can positively impact the performance of healthcare firms, enabling the sharing of resources, knowledge, and best practices. Collaborative strategies can lead to a more efficient use of available resources (Papastathopoulou & Hultink, 2012) and cooperation between competitors emerge as a response to regulations and policies established by formal institution agents (Czakon et al., 2020). Thus, the performance of firms in the healthcare sector is directly related to the regulatory environment established by formal institution agents. Efficient adaptations to regulations can enhance performance, while non-compliance may lead to sanctions and negatively impact operations (Monticelli et al., 2023).

The Influence of Formal Institution Agents on the Coopetition Network and Firm’s Performance

Coopetition depends on elements of the context (Czakon et al., 2020) that act as drivers (Bengtsson et al., 2016). For instance, the level of maturity and technology level of the industry influence coopetition for innovation (McCarthy et al., 2018). Additionally, Barretta (2008) considers the contextual conditions and how competition and cooperation evolve from the role of a regulatory body in balancing competitive and cooperative incentives. Some institutions can intermediate and consolidate interorganizational relationships (Y. Luo, 2005). Institutions generally differ between industries, regions, or value chains (Bouncken et al., 2018), but they invariably affect the industry and legitimize firms’ decisions.

Formal institution agents, particularly those that are public authorities, play a role in stimulating coopetitive strategies between players (Kylänen & Rusko, 2011) while developing deliberate or unintentional strategies (Mariani, 2018). Indeed, public agents help build trust among stakeholders and push or induce them into coopetition. Hidalgo et al. (2022) demonstrated the impact of formal institution agents on value creation within the value network, thereby fostering strategic entrepreneurial decisions in an organic food product chain. At the same time, in the healthcare sector, Peng and Bourne (2009) showed that intense face-to-face competition between two Taiwanese hospitals led to network formation and subsequently created opportunities for cooperation at the network level, fostering coopetitive strategies. On the one hand, competition improved cost efficiency, facilitated the adoption of advanced medical technologies, and enhanced public relationships for both hospitals and networks. On the other hand, cooperation reduced the duplication of healthcare services through cross-patient referrals. These results suggest that competition is valuable in the Taiwan healthcare industry not only for its direct benefits, such as efficiency and quality improvement but also for fostering coopetitive strategies within and between networks.

Coopetitive strategies target different objectives (Dorn et al., 2016) according to each country’s healthcare system, depending on the dynamics, complexity, fragmentation, and specialization of each setting. For example, Yanamandra (2018) proposed an integrative healthcare supply chain model in which mutual trust and cooperation result in customer satisfaction and cost reduction.

Governments play a pertinent role to play in monitoring and defining the best leverage of resources in the healthcare industry, particularly regarding relations between different stakeholder groups (Nakanishi, 2020; Raus et al., 2018). Thus, regulatory authorities, or formal institution agents, influence coopetition among private healthcare providers because they monitor these providers and authorize them to operate. The agency stimulates competition by monitoring regulatory compliance and sanctioning those that underperform. Authorizations to operate implicitly stimulate cooperation since they enable firms to cooperate to reduce costs and negotiate with suppliers and even with the agency itself. Regulatory agencies are thus institutions that can stimulate private healthcare providers to work together to obtain better results by sharing resources and/or setting collective objectives (Barretta, 2008). They also create shared patterns that orient behavioral rules and joint procedures that constitute formal institutional logic (North, 1990) and manage the intrinsic tensions of coopetition networks (Bengtsson et al., 2016).

Scholars have demonstrated that coopetition impacts firm performance, sometimes by directly analyzing sales volume, market share, and return on investment (Bouncken & Fredrich, 2012; Crick, 2018; Ritala, 2012). In the healthcare sector, cooperation enables participants to utilize resources more efficiently, facilitates knowledge exchange, and enhances the quality of care, operational efficiency, and financial performance. Concurrently, policymakers promote competition to reduce costs, and enhance access, and the quality of health providers. Nevertheless, the study of Mascia et al. (2012) identified a positive correlation between hospital competitive interdependencies and their inclination to collaborate, indicating that the emergence of managed care and the introduction of market forces into healthcare systems do not prevent the formation and development of local interhospital collaborative networks.

Ritala (2012) found that coopetition alignment positively impacts firm performance in uncertain markets or under pressure from excessive network externalities. Coopetition is a positive and significant variable that can moderate the relationship between entrepreneurial marketing orientation and financial performance (Crick et al., 2021). However, previous studies have shown that coopetition has a quadratic relationship with financial performance (Crick & Crick, 2021b). This shows that firms could experience adverse outcomes and reduced financial performance if they neglect their coopetitive strategies due to tensions and a diminished ability to develop a sustainable competitive advantage because of sharing excessive volumes of information, knowledge, or equipment with rivals (Crick & Crick, 2021b; Gnyawali & Ryan Charleton, 2018; Raza-Ullah, 2021). Along the same lines, research findings published by Pekovic et al. (2020) indicate that firms that cooperate with rivals perform better than non-cooperative firms. However, coopetition improves economic performance but can also decrease the beneficial effect of collaborating with non-rival partners. Le Roy and Czakon (2016) emphasize that various lenses are needed to understand the coopetition-performance relationship. Despite scholars’ agreement about the positive impact of coopetition on firm performance, this relationship has been studied little in the healthcare sector. Thus, we proposed to test the relationship between coopetition, formal institution agents and performance. Therefore, we propose the following hypotheses:

H1: The participation in networks of formal institution agents improves the coopetitive strategy in the healthcare sector.

H2: Participation in networks of formal institution agents is positively related to the performance of healthcare firms.

Coopetitive Strategies

Coopetition is interpreted as a concurrent strategy of cooperation and competition among firms or as a dynamic process in which players from the market produce value together out of cooperative interaction while at the same time competing to obtain a slice of that value (Bengtsson & Kock, 1999; Padula & Dagnino, 2007). It is recognized as a paradoxical, multi-faceted, multilevel phenomenon that aims to understand the strategy used in firm relationships (Chen, 2008; Gnyawali & Park, 2009).

The growing interest is gradually enriching the pool of coopetition knowledge with new qualitative findings and quantitative results. Klimas et al. (2023) identified 10 main reference theories, with game theory, resource-based view, and the network approach being the most relevant. They highlight those networks’ high importance due to their features and positions. Thus, to explore competitive advantages and access and gain new knowledge, it is necessary to build coopetitive relationships through networks (Bengtsson & Kock, 1999, 2000; Rusko, 2014; J. Yang & Zhang, 2021; X. Yang, 2020). Multiple theoretical frameworks have proposed analysis of several levels of drivers and outcomes, as they corroborate with the idea of coopetition as a complex phenomenon (Gnyawali & Park, 2009).

Regarding coopetitive strategy drivers, it can be motivated for different reasons. For instance, common vision and goals and mutual benefits (Zineldin, 2004) since market results are gathered at a higher level than the own firm’s results, such as increment in the size of the market, market creation, improved utilization of resources, reduction of cost, split risks, scale economy and innovative measures (Gnyawali & Park, 2009; Ritala, 2012) and network externalities in an industry (Pellegrin-Boucher et al., 2013). Market commonality and resource asymmetry among companies place coopetition at its maximum level. Market commonality connects better with competition, while resource asymmetry is more linked to cooperation (Hung & Chang, 2012).

The outcomes, coopetition allows firms to achieve scale and scope in the markets; reduce the learning curve; develop qualified labor; decrease time in innovation and technological solutions; diminish and sharing risks; bargain power increase; and develop strategic flexibility (Cygler, 2009; Zineldin, 2004). Sometimes, coopetition can also show negative results, such as tensions, power imbalances, opportunist behavior, knowledge leakage (Lascaux, 2020; Tidström, 2014) and a damaging effect on innovation (Nieto & Santamaría, 2007). However, studies have generally proved that higher performance is achieved with coopetition, mainly regarding the sales volume, market share, return on investment, and innovation (Bouncken & Fredrich, 2012; Crick, 2018; Ritala, 2012).

Coopetitive strategies aims to leverage resource and knowledge sharing, provide cost reduction, increase operational efficiency, stimulate joint innovation, enhance adaptability to market changes, and generate increased customer satisfaction. Coopetitive strategies outcomes leverage a better firm performance compared to their competitors (Monticelli et al., 2023; Mwesiumo et al., 2023). Within the healthcare sector, van den Broek et al. (2018) conducted research on the imperative for Dutch hospitals to compete with others in the same geographic area to attract and retain talented employees due to considerable labor shortages. According to their findings, establishing partnerships among the hospitals and creating local talent pools emerged as coopetitive strategies that enhanced firm performance. Thus, the subsequent hypothesis can be acknowledged:

H3: Coopetitive strategy improves the performance of healthcare firms.

Figure 1 illustrates the proposed research model.

Figure 1.

Research model.

Method

The study employed a quantitative research approach, utilizing multivariate statistical techniques in SmartPLS v. four software. Initially, the research involved conducting a Partial Least Squares Structural Equation Modeling (PLS-SEM) analysis. This step was crucial for validating the measurement model and affirming the interrelations amongst the constructs, thereby testing the proposed hypotheses. Subsequently, a Necessary Condition Analysis (NCA) was implemented to ascertain whether coopetition serves as a crucial determinant and a requisite condition for enhancing the performance of Brazilian healthcare firms.

PLS-SEM is widely recognized and utilized across various disciplines within the social sciences, gaining prominence for its effectiveness in model testing, theory building, and hypothesis validation (Hair et al., 2019). Diverging from covariance-based structural equation techniques, PLS-SEM uniquely estimates partial model structures. It achieves this by integrating principal components analysis with ordinary least squares regressions (Hair et al., 2019). The methodology is particularly known for its causal-predictive focus, emphasizing prediction, which makes it a suitable methodological choice for this study. Additionally, PLS-SEM is recommended for models where the data may not exhibit a multivariate normal distribution or when the sample size is relatively small (Ringle et al., 2014).

Necessary Condition Analysis (NCA) complements PLS-SEM by utilizing the composite scores of each construct. It aids in identifying necessary conditions by analyzing scatter plots that plot dependent against independent variables (Richter et al., 2020). The combined application of these two methodologies facilitates the validation of the path model and aids in generating managerial interpretations that are grounded in empirical evidence.

Context of Analysis

This study considers that intervention by a formal institution agent influences firm behavior, coopetitive strategies, and performance. We chose the Brazilian healthcare industry to test our proposition because formal institution agents coordinate this sector. They are also policymakers that influence healthcare companies’ strategies. Regulatory agencies, such as the National Supplementary Health Agency (ANS) and the Brazilian Health Regulatory Agency (ANVISA—Agência Nacional de Vigilância Sanitária) are the main formal institution agents in the Brazilian healthcare sector. They are responsible for control and monitoring of private healthcare in Brazil, stimulating coopetition between healthcare plan operators and health insurance firms to obtain better results and efficiency. Although the Brazilian Government does provide public healthcare, private healthcare firms play a relevant role in supplementing public services.

The Brazilian healthcare sector is a complex and fragmented industry, with asymmetric bargaining power both between different firms and between firms and the Government. There are more than 1,000 health plan operators and health insurance firms in Brazil. Nevertheless, 29% of patients are clients of the seven biggest private healthcare firms (PricewaterhouseCoopers Brasil Ltd. (PwC Brasil), 2013). Commercial associations and industrial bureaus such as the Brazilian Health Plans Association (Associação Brasileira de Planos de Saúde [ABRAMGE], 2021) represent the healthcare firms, aiming to ensure the sustainability of the private healthcare market. Other examples of formal institution agents that foster networks in the sector include the Private Hospitals National Association (ANAHP), the Group Medicine Companies’ Industry Association (Sindicato Nacional das Empresas de Medicina de Grupo [SINAMGE]), the healthcare workers’ trade union (Sindicato dos Hospitals e Clínicas [SINDIHOSPA]), and professional representative bodies such as local and national medical boards (e.g., the Conselho Federal de Medicina [CFM]).

Sample

We collected data using questionnaires sent to 737 firms between March and June of 2021. The raw response rate was approximately 20%. The sample comprised 149 firms from the Brazilian private healthcare system: health plan operators that cover inpatient medical treatment costs or health insurance firms that cover diagnosis and outpatient treatment costs. The sample size equates to about 13% of all Brazilian healthcare firms and attends the indications of Churchill (1979) and Hair et al. (2009), at least five respondents per item on the scale. The informants were managers at tactical and strategic levels who interface with formal institution agents. Twenty-four percent of the sample were small or medium firms (up to 500 employees) and 76% were medium or large firms (over 500 employees). The respondents’ average age was approximately 43 years, 53% were men, 47% were women, 58% were in management positions, and 42% were directors.

Measures

The research instrument comprised three sections with seven-point Likert response scales to collect data on the three latent variables in the model illustrated in Figure 1. We adopted an established scale from the literature to measure the dependent variable, Overall Performance (PERTOT). For the independent variables Network of Formal Institution Agents (NWFI) and Coopetition (COOP) we created scales based on the findings of a literature review. We also validated the content of the scales with three executives who work in companies in the health sector. These executives evaluated each item separately and made assessments individually. Next, they discussed and evaluated the results of the individual analyses together. We therefore used a panel of expert judges to appraise the face validity and scale reliability (Narver & Slater, 1990; Zaichkowsky, 1985) of the instrument used in the qualitative stage. Based on these discussions, we then made some adjustments to the questionnaire to (i) improve comprehension of the coopetition variable; and (ii) mention formal institution agents in questions about the network variable.

Dependent Variables

Overall Performance (PERTOT)

The performance measurement was based on the EXPERF scale (Zou et al., 1998) adapted to the domestic market. The variables used are financial export performance, strategic export performance, and satisfaction with export venture.

Independent Variables

Networks at Formal Institution Agents (NWFI)

Networks fostered by formal institution agents generate arrangements that can induce coopetitive strategies. To measure this variable, we used a scale based on work by Pla-Barber and Escribá-Esteve (2006) and He and Wei (2013). However, we included additional questions related to variables such as learning, cost reduction, knowledge development, and the influence of government with the support of the formal institution agents. These changes were made to the original scales because our research focuses on understanding the relationship between NWFI, coopetition mediated by formal institution agents, and performance, considering FIAs as industry and government agencies and bureaus.

Coopetition (COO)

Coopetition measurement considers both competition and cooperation, thus questions cover shared goals, skills transfer, and complements being identified in the industry (Choi et al., 2009), reciprocity (Muijs & Rumyantseva, 2014), and trust (Morris et al., 2007; Perera et al., 2015). The questions focus on the following aspects: (i) market, (ii) commitment, (iii) mutual benefits, (iv) knowledge, (v) innovation, (vi) trust, and (vii) strategy.

Control Variables

(a) Firm age (AGE); (b) firm size in terms of number of employees (EMP); and (c) firm size in terms of revenue (REV). This kind of industry manifests heterogeneity and complementarity of resources (Hung & Chang, 2012) and of the activities and influence of formal institution agents (Hidalgo et al., 2022). Firm size can be related to the likelihood of accessing resources and markets and the potential for closing deals with other firms using both cooperation and coopetition approaches. A firm’s size can also be indicative of its expectations of obtaining resources and accessing markets, determining its possibilities for engaging in cooperative strategies with competitors. For example, SMEs usually have less access to resources and markets than large firms (Musteen et al., 2010).

Results of Measurement Model

Scale Purification and Assessment of the Measurement Model

We did not find problematic items that needed to be excluded because of kurtosis or skewness. We verified the initial descriptive statistics for the variables before performing any advanced (multivariate) statistical procedures. For all three dimensions in the model, most items had means above the center of the measurement scales and relatively low standard deviations (SDs).

A partial least squares structural equation modelling (PLS-SEM) using the SmartPLS 4.0 software was the technique to identify and confirm the variables of each model component. The initial proposition with the 33 variables, being 14 variables to Coopetition (COO), 10 variables to Networks at Formal Institution Agents (NWFI) and nine variables to Overall Performance (PERTOT). Results from the assessment of the measurement model reduced the model to 27 variables (10 to Coo, 6 to NWFI and 9 to PERTOT) since we maintained only variables with a loading factor above .7 (Table 1).

Table 1.

Scales and Cross Loading Factor.

My firm…	Variable	COOP	NWFI	PERTOT
Develops conjoint actions with my competitors to achieve mutual benefits.	CO06	.832	.567	.478
Has a collaborative behavior in the relationship with its competitors	CO01	.822	.535	.501
Is known for the reciprocity in the relationship with the competitors	CO04	.817	.507	.411
Aligns strategies with its competitors	CO08	.805	.566	.485
Is known for its trust in the relationship with its competitors.	CO03	.793	.494	.387
Develops actions with its competitors to learning and experience exchange	CO02	.784	.544	.388
Is recognized for its commitment to the relationship with its competitors	CO05	.778	.496	.369
Improves competitiveness through conjoint actions with its competitors	CO09	.740	.593	.395
Shares information and knowledge with its competitors	CO13	.737	.567	.360
Shares strategic goals with its competitors.	CO10	.712	.388	.395
Has benefits such as learning and dissemination of technical knowledge with the help of formal institutions agents.	NWFI05	.570	.863	.441
Aims to use networks and connections with industrial agencies or bureaus in various levels of the government, both in the domestic market and in the international market.	NWFI03	.547	.826	.453
Has benefits such as the creation of intelligence on domestic and international markets with the help of formal institutions agents.	NWFI08	.555	.794	.342
Aims to use networks and connections with officials in domestic and international regulatory and supporting organizations, such as tax bureaus, state banks, commercial administration bureaus, and universities.	NWFI04	.456	.788	.469
Has benefits or enhances its network through trade associations, research centers, associations, or unions	NWFI01	.623	.779	.476
Has strategic and networking formatting benefits with the help of formal institutions agents.	NWFI07	.468	.744	.316
Has strengthened its strategic position in the last 3 years.	PE02	.509	.486	.937
Has generated a high volume of sales in the last 3 years.	PF03	.511	.512	.934
Has reached a satisfactory performance in the last 3 years	PS01	.479	.461	.933
Has improved its competitiveness in the last 3 years.	PE01	.532	.553	.932
Has significantly increased our market share in the last 3 years.	PE03	.491	.483	.932
Has completely met the expectations with initiatives in the domestic market in the last 3 years.	PS03	.501	.421	.903
Is satisfied with initiatives in the domestic market in the last 3 years.	PS02	.442	.411	.898
Has generated a high volume of sales in the last 3 years.	PF02	.447	.471	.865
Has made satisfactory profits in the last 3 years	PF01	.440	.471	.812

The measurement model presented convergent validity and reliability (Table 2). The composite reliability and Cronbach’s alpha values were more than .9 and .8 respectively, which established satisfactory internal reliability (Hair et al., 2011).

Table 2.

Composite Reliability and Discriminant Validity.

Latent variable	(1) COO	(2) NWFI	(3) PERTOT
1. Coopetition (COO)	.783
2. Network of Formal Institution Agents (NWFI)	.676	.800
3. Overall Performance (PERTOT)	.536	.526	.906
Cronbach’s alpha	.929	.887	.972
Composite reliability	.940	.914	.976
Average variance extracted (AVE)	.613	.640	.821

The discriminant validity between the constructs was based on the Fornell–Larcker (1981) criteria. The variance extracted from each construct (main diagonal of Table 1) is greater than the variances shared between the constructs (squared correlation—in the other cells of Table 1). Also, we confirm that the model has discriminant validity through the Heterotrait–Monotrait Ratio (HTMT) that showed values below .9.

Common Method Variance

Results originating from the same research data, method, and context may be subject to common method bias. To deal with this potential bias, we adopted an ex-ante and an ex-post strategy (Chang et al., 2010). Our ex-ante strategy was to use different information sources to obtain the key measures, administering the survey to more than two representatives from the tactical and strategic levels of firms in the Brazilian private healthcare system. Moreover, we also used a ex-post strategy, a Harman’s single-factor test by loading all variables into a single factor in EFA to check the data variance attributed to each single factor. We concluded that no single factor explained more than 40% of the total variance (Podsakoff et al., 2003). Following Kock (2015), we proceeded a full collinearity assessment approach all VIF values were lower than the 3.3 threshold, then we assumed the data are free from Common method bias (CMB).

Finally, we also collected objective profitability data from a group of companies and correlated them with the subjective performance data. The correlation analysis (Pearson correlation = .586, significant to .01) indicated that the subjective variable was positively correlated with objective performance data (PERTOT).

Results from PLS-SEM

The structural model was assessed using 5,000 bootstrap resamples and the confidence intervals at 95%. Results indicated good fit and predictive relevance. The coefficients of determination R² were COO = .457 and PERTOT = .336, which means moderate values according to Hair et al. (2011). We used the PLSPredict to verify the model’s predictive capacity. The model has Q² (COO) = .440 and Q² (PERTOT) = .263. Results indicated a robust model predictive relevance to coopetition and moderate to Overall Performance based on the indications of Urbach and Ahlemann (2010).Figure 2 shows the Path coefficients.

Figure 2.

Structural model.

The bootstrap resamples method showed the three paths tested were supported (p < .05). The participation in networks of formal institution agents improves the coopetitive strategy in the healthcare sector Coopetition (β = .332, t = 3.472, p < .001), coopetitive strategy improves the performance of healthcare firms (β = .676, t = 10.836, p < .000), and Participation in networks of formal institution agents is positively related to the performance of healthcare firms (β = .301, t = 2.972, p < .003; Table 3).

Table 3.

Results of the Path Coefficients.

Hypothesis		Original sample (O)	Standard deviation (STDEV)	t-Statistics (\|O/STDEV\|)	p-Values
H1: The participation in networks of formal institution agents improves the coopetitive strategy in the healthcare sector	COOP → PERTOT	.332	0.096	3.472	.001	Supported
H2: Participation in networks of formal institution agents is positively related to the performance of healthcare firms	NWFI → PERTOT	.301	0.101	2.972	.003	Supported
H3: Coopetitive strategy improves the performance of healthcare firms	NWFI → COOP	.676	0.062	1.836	.000	Supported

None of the control variables—firm age, firm size as employee headcount, or firm size measured as revenue—had a significant relationship with performance. Generally, larger and more experienced firms have better performance than smaller firms because they have access to more resources (Musteen et al., 2010). However, the Brazilian healthcare sector is a highly regulated and heterogeneous industry in which firms form strong relationships with other firms in the sector and with formal institution agents to achieve market fit and offer their value proposition in the market. Put simply, the regulator targets maximum coverage of the population, and the firms target maximum market share. Consequently, this relationship may be more relevant to the firm’s performance than the firm’s characteristics.

Discussion

Our findings support the positive influence of networks formed by formal institution agents on coopetition and performance in the healthcare sector (H1 and H2). The results establish a positive and significant association between coopetition and the performance of healthcare firms as well (H3). The first model proposition embodied 33 indicators. The validated model held fixed only 25 indicators. Moreover, the participation in networks of formal institution agents directly and indirectly impacts the performance of healthcare firms.

Prior research has found that formal institution agents play a predominant role in promoting or facilitating networks and stimulating coopetitive strategies, mainly in already robust industries. Formal institution agents aim to increase the competitiveness of firms by developing learning and relationship networks, reducing costs and promoting firm internationalization (Monticelli et al., 2021). According to our findings, formal institution agents improve the healthcare industry’s competitiveness by generating benefits for firms such as cost savings, strategy formulation, and development of market intelligence. Moreover, they represent the firms in dealings with the government and facilitate access to new resources and technologies (Monticelli et al., 2021). Consequently, formal institution agents encourage coopetitive strategies between healthcare firms, which in turn strive to capture value from these benefits.

There are several different perspectives on the antecedents of coopetition. Perera et al. (2015) found four factors that affect the success of coopetition and firm performance: trust, mutual benefits, resource compatibility, and commitment. However, power balance positively moderates this relationship between factors and coopetition. Dorn et al. (2016) state that market conditions and dyadic and individual factors influence the relationship between coopetition and performance. Recently, Czakon et al. (2020) found that strategic rationale and coopetition mindset orientation are the behavioral antecedents of coopetition, while cooperation, trust, and experience in coopetition are the elements that make up coopetition mindset orientation.

Earlier studies have suggested there is a positive relationship between coopetition and performance (Crick, 2018; Crick & Crick, 2021a; Ritala, 2012). Coopetition is especially beneficial when market uncertainties are high, improving the firm’s market performance and innovative performance (Ritala, 2012). However, excessive coopetition and competitive aggressiveness can have a negative influence on performance, being a cause for concern about opportunistic behavior (Crick & Crick, 2021a; Gnyawali & Park, 2009). Thus, researchers have found mixed results, showing that attempts to measure the results of coopetition have so far been inconclusive (Jakobsen & Steinmo, 2016). In contrast with these studies, our findings show that the influence of networks fostered by formal institution agents is the main antecedent to establishing a coopetitive strategy among firms. This understanding complements Czakon’s (2018) position that coopetition can be induced by partner behaviors, competitor behaviors, or regulator decisions. Nevertheless, our findings showed a mixed influence from formal institution agents and the networks that develop from their relationships with healthcare firms.

Moreover, our results indicate that firms participating in the networks fostered by formal institution agents achieve improved performance. Our finding aligned with previous studies that have considered the influence of embeddedness in social networks, industrial competitiveness, and the institutional environment (Czakon, 2018). By our results, the performance of healthcare firms receives a double positive effect if the firm participates in networks of formal institution agents since they foster coopetitive strategies. Nevertheless, participation alone cannot be sufficient for firms to attain superior performance, particularly in an industry as highly regulated as the Brazilian healthcare sector. Thus, to confirm this finding, we run a Necessary Condition Analysis (NCA) in the Smart PLS software. The results showed coopetition effect size of coopetition on the performance was .158 and significant with a permutation p-value of .001. However, NWFI’s effect size on Performance was .069, but non-significant (Permutation p-value .105). Thus, by the results of PLS-SEM combined with NCA, based on Richter et al. (2020), we concluded that coopetition is a significant determinant and a necessary condition to improve the performance of Brazilian healthcare firms. Nevertheless, participating in the networks of formal institution agents is a significant determinant but not a necessary condition to improve performance.

For Brazilian healthcare firms, it can be difficult to achieve superior performance because they deal with the government, which engages in measures to transfer the burden of financing healthcare expenses to out-of-pocket expenditures by families. There is, therefore, a complex relationship between the public and private sectors based on a provision of an essential service to the population, which imposes a more prescriptive role on the formal institution agents and, consequently, creates an incentive for firms to develop coopetitive strategies to deal with their impositions. Consequently, coopetition may be a strategy resulting from the regulatory changes imposed by formal institution agents (Nakanishi, 2020), since firms develop mechanisms together to overcome restrictions imposed by regulatory agencies and enlarge their strategic options and bargaining power against them (Monticelli et al., 2023).

Our findings bear significant implications for both managerial strategies and the formulation of public policy. The government’s decision to transfer the burden of financing health expenses to families aims to alleviate fiscal burdens. As a result, the government may face pressure from society, especially if the increase in family expenses creates financial difficulties for the most vulnerable segments of the population. This finding endorses the results of previous research in the context of Brazilian health, such as Massuda et al. (2018) and Baird (2019). Moreover, for healthcare firms, the imposition of transferring part of the costs to families can pose operational and strategic challenges. Government policy have prompted adjustments in strategic decision-making, fostering cooperation among competing firms to effectively address the escalating demands of the population. Consequently, our results indicate that coopetition emerges as a response to regulatory constraints (Nakanishi, 2020). Moreover, the effectiveness of coopetitive strategies among healthcare providers may have direct implications for the availability of services and options for the population, thus shaping their experiences within the healthcare system. This consequence was researched by Monticelli et al. (2023), who identified institutional dysmorphia which is a distortion of a formal institution agent’s primary role that influences the competitors’ strategic decisions.

Additionally, our findings enrich the existing knowledge on the subject. Our results demonstrated that the age or size of the firm, in terms of number of employees and revenue, were not significant differentiators of appropriation of value by healthcare firms and, consequently, of their performance. This result differs from previous studies (J. Yang & Zhang, 2021; X. Yang, 2020) because Brazilian highly regulated industry induces firms to develop coopetitive strategies to maintain competitiveness, mainly in defense against regulatory changes imposed by the government. Superior firm performance is dependent on how a firm deals with the institutional environment to reconcile competitive and cooperative pressures. At this point, the greater the interaction, the greater the possibility of improving the performance of products, services, customer relationships, gains in productivity, efficiency, and quality, and it would not be possible to achieve this in isolation, regardless of firm age or size. This finding is compatible with Raza-Ullah’s (2021) explanation of how coopetition contingencies affect performance. He showed that moderate and high levels of both trust and distrust result in better performance from coopetition strategies than when one partner has a low level and the other a high level of trust.

Concluding Remarks

This research analyzed the influence of coopetition fostered by formal institution agents on the performance of private health plan operators in Brazil. This country’s institutional environment impacts businesses’ strategies, remodeling how firms develop competitive and cooperative strategies and, consequently, coopetition. Therefore, coopetition and the institutional environment are related in multiple ways.

Our first contribution highlights that networks facilitated by formal institution agents precede firms’ adoption of coopetition to enhance performance, especially in highly institutionally regulated environments. In highly institutionally regulated environments, coopetition can be a deliberate response to the actions of formal institution agents (Czakon et al., 2020). However, it is relevant for the government to find a balance between regulating the sector and encouraging the delivery of healthcare provision to the population, especially in emerging countries with poor infrastructure.

Our second contribution shows that regulatory policy affects firms’ strategies and behaviors. Policymakers, acting as formal institution agents, advocate competition to cut costs and enhance service quality. In these terms, coopetitive strategies are a relevant option for dealing with highly regulated markets in emerging economies that suffer from fragile institutions. This result sheds light on the organizational dynamics within the Brazilian private healthcare sector.

Our third contribution underscores that formal institution networks alone do not guarantee performance improvement. Healthcare firms must also develop coopetitive strategies to create and capture value within these relationships. While formal institution networks act as mediators and contribute to better outcomes, the adoption of coopetitive strategies is necessary for enhancing the performance of Brazilian healthcare firms, especially in regulated markets and emerging economies with fragile institutions.

On a managerial level, for policymakers our study details the opportunities for and challenges to improving the competitiveness of the healthcare sector, depending on the institutional environment. For healthcare firm managers, our study details opportunities for developing relationship strategies, including coopetition, resource optimization, and the pursuit of market opportunities. These considerations are particularly relevant within the institutional environment studied, with a focus on the regulatory context imposed by the government through formal institution agents.

Limitations and Directions for Future Research

This research is subject to boundary conditions because it was conducted in just one country. Research is needed that compares different countries to provide insights into the level of influence on industry performance of the relationship between formal institution agents and coopetitive strategy. The study is also limited by the cross-sectional design since respondents’ replies are specific to the current scenario in the industry. Moreover, it is necessary to conduct studies of larger samples from other industries, because the number of firms in the Brazilian healthcare sector is relatively low, resulting in a limited number of respondents.

Further avenues for investigation are revealed when a study is completed. Firstly, inter-firm competition should be considered in the light of and contrasted with the inter-cluster competition. Secondly, the contextual approach to coopetition enables us to analyze assets of value within the chain of agents. Finally, another prominent research avenue would be to explore how decisions of a political nature influence the institutions that coordinate the healthcare sector, setting out new viewpoints on coopetition in a regulated industry

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The first and fourth authors has received grants from Foundation for the Support to Research in the State of Rio Grande do Sul (FAPERGS).

Ethical Approval

Ethical approval for this type of study is not required by our institute.

ORCID iDs

Jefferson Marlon Monticelli

Ivan Lapuente Garrido

Adriana Fum Chim-Miki

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

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Formal Institution Networks and Coopetition: Insights from the Brazilian Private Healthcare Industry

Abstract

Keywords

Introduction

Theoretical Background

The Influence of Formal Institution Agents on the Coopetition Network and Firm’s Performance

Coopetitive Strategies

Method

Context of Analysis

Sample

Measures

Dependent Variables

Overall Performance (PERTOT)

Independent Variables

Networks at Formal Institution Agents (NWFI)

Coopetition (COO)

Control Variables

Results of Measurement Model

Scale Purification and Assessment of the Measurement Model

Common Method Variance

Results from PLS-SEM

Discussion

Concluding Remarks

Limitations and Directions for Future Research

Footnotes

Declaration of Conflicting Interests

Funding

Ethical Approval

ORCID iDs

Data Availability Statement

References